mojiTMJ - Overview

🚀 Welcome to Moji's Data & AI Universe!

Where Data Meets Intelligence 🧠✨

🎯 About Me

class DataArchitect:
    def __init__(self):
        self.name = "Moji"
        self.role = "Data & AI Architect"
        self.location = "Milan, Italy 🇮🇹"
        self.status = "Freelance Professional"
        self.specialization = "Data & AI Engineering"
        self.motto = "Turning Data into Intelligence"
        
    def get_current_focus(self):
        return [
            "Building scalable data pipelines",
            "Designing AI architectures",
            "Optimizing ML workflows",
            "Chess strategy optimization 🏁"
        ]

Core strengths:

Event-driven lakehouse governance with data contracts and quality gates
MLOps on Azure, AWS, and hybrid GPU clusters with FinOps discipline
Graph analytics with Neo4j and feature engineering for fraud/recsys
Observability, SLOs, and cost-aware architecture reviews

🛠️ Tech Arsenal

🚀 Featured Impact

Event-driven lakehouse – Cut batch ETL runtime by 35% while serving 5B+ monthly events for downstream analytics.
Multi-cloud LLM platform – Deployed resilient inference across Azure + AWS with 99.9% uptime and autoscaling GPU clusters.
Real-time fraud signals – Built streaming graph features on Neo4j that reduced false positives by 22%.
LLMOps control plane – Established evals + rollout guardrails to keep latency steady during 10x traffic spikes.

📊 GitHub Analytics

🎯 What I'm Working On

🎯 **Current Focus (with outcomes)** - Accelerating ingestion and transformation to keep nightly SLAs **< 45 minutes** for enterprise BI. - Shipping a **feature store** that cuts ML model drift by giving teams fresher signals **2x faster**. - Hardening **MLOps** with blue/green rollouts and **p95 latency < 120ms** for customer-facing APIs. - Coaching teams on **event-driven architectures** and **data contracts** to reduce rework by **30%**. - Piloting **RAG for analytics** to surface trusted metrics with **<1% hallucination** in exec dashboards.

🏆 Achievement Unlocked

🎾 Tennis Enthusiast	♟️ Chess Strategist	🔧 Pipeline Optimizer	🌍 Multi-Cloud Expert
Serving aces on and off the court	Always thinking 5 moves ahead	Making data flow like poetry	Architecting across all clouds

🎮 Fun Zone

🎲 Random Dev Joke

🏃‍♂️ Current Status

🔥 Building the future of data architecture
🎾 Perfecting my backhand
♟️ Analyzing chess positions
☕ Fueled by espresso (it's Milan, after all!)

Chess strategy sharpens my design thinking, and tennis keeps my iteration cycles fast.

📝 Latest Writing & Talks

graph TD
    A[🧠 AI Architecture] --> B[Data Pipeline Optimization]
    A --> C[ML Model Deployment]
    B --> D[Real-time Analytics]
    C --> E[Scalable Solutions]
    D --> F[🚀 Production Ready]
    E --> F
    
    style A fill:#1E3A8A,stroke:#3B82F6,stroke-width:2px,color:#fff
    style F fill:#059669,stroke:#10B981,stroke-width:2px,color:#fff

Data Contracts in Practice – How schema governance cut rework across 20+ teams. (Link: coming soon) Scaling LLM Inference on GPUs – Patterns that kept costs predictable during traffic spikes. (Link: blog / deck) Graph Features for Fraud – Why Neo4j centrality scores boosted detection precision. (Link: notebook)

📈 Contribution Graph

🤝 Let's Connect!

💬 "Always up for a challenge—whether it's optimizing data pipelines or finding a killer move in chess!"

📬 Availability: Open for freelance architecture sprints and technical leadership engagements. 🔗 Reach out: LinkedIn • Email

_{🚀 Built with passion in Milan | 🎯 Crafted for the GitHub community}